摘要
为提高浊音端点检测的准确率和效率,提出一种基于循环自相关函数的检测方法。设计语音的循环自相关函数,利用该函数与短时能量定义状态及转移损失函数,通过动态规划方法判别浊音的端点,并采用不同分类判断方法与检测函数进行测试。实验结果表明,与基于能量及谱墒的方法相比,该方法的抗噪性能较好。
To enhance the accuracy and efficiency of endpoint detection,a detection method based on Circular Autocorrelation Function（CACF） is proposed.The method calculates CACF of the speech,defines the loss functions of state and state transforming with the values of CAF and the short-term energy,and decides the voiced endpoints with dynamic programming.Experimental results display several comparisons including that among detections using the traditional Autocorrelation Function（CAF）,average magnitude difference function and the CACF,which demonstrate that CACF improves the accuracy and efficiency of endpoint detection and better resists the acoustic noise than the traditional energy and spectral entropy method.
出处
《计算机工程》
CAS
CSCD
北大核心
2011年第22期5-7,共3页
Computer Engineering
基金
国家部委基金资助项目
关键词
浊音
端点检测
循环自相关函数
短时能量
动态规划
损失函数
voiced sound
endpoint detection
Circular Autocorrelation Function（CACF）
short-term energy
dynamic programming
loss function
